A 3-Step Framework to Regain Control
Supply chain planning doesn’t fail because teams aren’t trying hard enough.
It fails when they’re aiming at the wrong things, with unclear decisions, overloaded KPIs, and scattered data.
Over years of consulting and implementation, we’ve seen one pattern repeat: Planning becomes reactive when clarity disappears.
To fix this, we’ve created a practical 3-part clarity loop:
Map the Decisions
Define the Right KPIs
Trace the Data You Need
Let’s break it down with real challenges—and what you can do instead.
1 Unclear Decision-Making: Everyone’s Busy, No One’s Steady
Problem: Most teams jump straight into forecasts, reports, and dashboards—without stopping to define the decisions they’re actually supporting. This creates noise instead of alignment. Meetings become repetitive, strategic gaps go unnoticed, and urgent topics override important ones.
Solution: Start with a 2D Decision Map. For every planning decision:
Plot its Importance (Y-axis)
Define its Time Horizon (X-axis: days/weeks/months/years)
This map surfaces where the organization is spending energy, and where it’s lacking ownership or structure. It helps teams distinguish between:
High-effort, low-impact distractions
Rare, high-impact strategic calls that need clear frameworks
Once decisions are mapped, everything else flows with more intention:
– KPIs align with purpose.
– Data needs become clearer.
– Meetings become focused on actual choices—not noise.
2. Overloaded KPI Dashboards: When Measurement Creates Confusion
Problem:
Dashboards are not the issue. The real issue lies in the uncontrolled growth of irrelevant KPIs. Too many organizations suffer from “KPI overgrowth”—a condition where metrics are added continuously, but rarely pruned. This often leads to:
Misaligned measurements across departments (e.g., Finance tracks margin, Supply tracks utilization, Sales tracks sell-out, each with different units and timeframes)
KPIs being chosen for convenience rather than relevance
Important meetings devolving into tactical firefights, with no one steering the strategy
The result is a planning environment where nobody is quite sure what to trust, or what to act on.
Solution:
To fix this, teams should conduct a structured 15-Minute KPI Audit:
List all KPIs currently being tracked (without omitting those that feel redundant)
Rate the trustworthiness of the data on a scale of 1 to 5
Tag each KPI to its corresponding planning process and time horizon
After the list is compiled and rated, each KPI must be evaluated using a simple but rigorous KPI Quality Gate:
Is the KPI actionable? In other words, if it changes, can someone actually make a planning or operational decision?
Is the KPI tied to a specific decision point or meeting? Every KPI must justify its existence by aligning with a real decision.
Is the data reliable enough to drive action? If confidence in the data is below 3 out of 5, the source must be fixed, or the KPI removed.
Finally, align KPIs with their appropriate time horizons:
Operational KPIs: Used daily or weekly (e.g., OTIF, Inventory Accuracy)
Tactical KPIs: Used in weekly or short-cycle planning (e.g., SKU Availability)
S&OP KPIs: Used monthly for cross-functional balancing (e.g., Forecast Bias %)
Strategic KPIs: Used quarterly or annually for long-term steering (e.g., CapEx ROI, Capacity Headroom %)
This process is not about reducing visibility, it’s about increasing relevance.
3. Scattered, Unreliable Data: The Silent Killer
Problem:
Even the most well-designed KPI framework will collapse if the data behind it is inconsistent, outdated, or buried in inaccessible systems. In most organizations, planning data is scattered across spreadsheets, siloed in disconnected tools, or buried deep within business intelligence platforms no one fully trusts.
Symptoms of this problem include:
Different departments pulling different results for the same KPI
Conflicting definitions for basic planning terms (e.g., “priority SKU” or “inventory coverage”)
KPIs that change depending on who created the report or which tool is used
Excel files that are copied, edited, and forgotten leaving no audit trail or clarity on ownership
Solution:
Use the refined KPI set from Step 2 as a starting point. For each one, conduct a Data Fitness Check by asking the following:
Where does this data come from? Identify the original source and trace it through any transformations or hand-offs.
Who owns this data? Assign clear responsibility for maintenance and validation.
Is it reviewed frequently enough? The review cadence must match the KPI’s planning horizon.
Is it accessible and structured? Data buried in narrative text, emails, or Excel tabs is not usable. Planners must be able to retrieve and interpret it quickly.
Once you have answers to the questions above, apply a Data Quality Test with four criteria:
Accuracy – Are the values correct and consistently reported?
Timeliness – Is the data updated often enough to support the planning cadence?
Completeness – Are any key values missing (e.g., locations, time buckets, SKU segments)?
Usability – Can the data actually be found, understood, and acted upon without extra effort?
If a data source fails more than one of these checks, it’s either not ready for use—or it needs immediate remediation. No decision should be made on data that cannot be trusted.
4. Final Thoughts
Planning clarity isn’t just about implementing new software or adding more dashboards.
It’s about putting the right structure in place to support effective decisions.
That structure starts with:
A shared view of the decisions that matter
A filtered, aligned set of KPIs tied to those decisions
Trusted, accessible data that enables action
When those three elements are connected, decision, KPI, and data planning stops being reactive and becomes a tool for real control, alignment, and growth.
